CREATING GROWTH CAPABILITIES

How and why do you make decisions?

Neuroscience explains that we have subconscious associations, beliefs and emotional triggers that come together to influence the way we behave. Quite separate is the area of big data, where prediction analytics and other software can reveal how people will behave without the existence of a single insight process.

When it comes to decision-making, neuroscience explains a quick, more intuitive style, whereas big data can drive a slower, more analytic style. Marketers will fall somewhere along this intuitive-versus-analytic decision-making spectrum; ask yourself where you sit predominantly.

Intuition-driven

If your instincts tend to guide you, recognise that you may disregard new data sources, using what's readily available and familiar to guide your swiftly made decisions. Moreover, if you're a user of the category you market, you may also rely heavily on your personal insight to guide conclusions.

If this is you, keep in mind that too much subjectivity may create a blind spot to actual and/or emerging customer behaviours that only large sets of objective data reveal.

As an example, marketers in South America noticed that consumers were washing their floors with washing powder. Naturally, marketing's first instinct was to launch a powder-based floor cleaning product. However, a look at the data revealed that most consumers were actually using washing powder for all their cleaning needs – they could afford only one cleaning product and were unlikely to buy a new floor cleaner merely because it was in a powder format.

As a marketer you may trust that your instincts are driven by consumer understanding, but recognise that "fast" does not always mean "good", and one's own experiences or instincts cannot tell the whole story.

Analysis-driven

If you are more analytical, you will relish the increase in available data today, have a systematic approach to its collection and analysis and see it as a vital element in decision-making.

Our washing-powder example could easily have worked the other way; an analysis-driven marketer looking exclusively at data showing a high volume of consumers using washing powder on their floors may also have seen this as hard evidence for launching a powder-based floor-cleaning line. However, being more closely connected to the consumer, with an understanding of their housekeeping, could intuitively have told these marketers that cost may play a role, prompting further digging into the data and a more sound decision.

The balance afforded by taking on board the learnings of both neuroscience and big data allows a marketer to identify his or her personal decision-making style and, therefore, their propensity to be either overly instinctive or to suffer from analysis paralysis. When it comes to homing in on a single consumer insight – or more usually, a range of insights – being equally influenced by neuroscience and data can, ultimately, help marketers make a better decision.

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